The recent advance in digital radiographic imaging systems, such as the flat-panel based direct digital radiographic (DR) systems (“A high resolution, high frame-rate, flat-panel TFT array for digital x-ray imaging,” Proceedings of SPIE Medical Imaging, Antonuk et al., vol. 2163, pp 118-128, 1994) and the storage phosphor based computed radiographic (CR) systems (“Introduction to medical radiographic imaging,” Eastman Kodak Company, 1993) etc, allow the separation and optimization of image acquisition, processing, and display processes individually. The image pixel data are manipulated during the image-processing step so as to optimize the image information acquired on the radiograph and to help the radiologists to better perceive even the subtlest diagnostic details. Optimizing diagnostic details depends on the knowledge of the location and characteristics of both diagnostically relevant and diagnostically irrelevant regions in the radiograph. The scope of this invention therefore relates to the automatic segmentation of a digital radiograph into anatomy (diagnostically relevant regions), foreground and background (diagnostic irrelevant regions).
FIG. 1(a) shows an example of a foot radiograph acquired with CR. The foot was exposed at three viewing angles A, B, C using the same storage phosphor cassette but at different cassette regions. The anatomy in this radiograph is the foot and is considered diagnostically relevant. The regions in the radiograph where x-rays directly expose the storage phosphor are diagnostically irrelevant, which are later referred to as the background or direct exposure region. Collimation was used during the x-ray exposure to reduce unnecessary radiation to the anatomy that is irrelevant to diagnosis and to confine the x-rays to a local region of the cassette. The regions in the radiograph collimated outside the x-ray radiation field are diagnostically irrelevant, which are later referred to as the foreground region.
The work of Barski et al. taught a method of determining the direct exposure regions in a radiograph (“Determination of direct x-ray exposure regions in digital medical imaging,” U.S. Pat. No. 5,606,587). However, this method uses a single value, namely background left point, to threshold the input image to generate a binary map. Although this method is suitable for the purposes for which it was intended, in the case when the direct exposure region has a large intensity non-uniformity, which can be caused by the non-uniform intensity distribution of the incident x-rays or by the exam requirements that need multiple views of the anatomy at different exposures levels another method may be needed. FIG. 1(b) shows an example of the result using Barski's method, which indicates that the background can be over-detected and under-detected at the same time. The thresholds used in this method also vary from one exam-type (bodypart and projection) to the other, which may not work well when exam-type information is unavailable.
Pieter disclosed a method to determine the foreground region in a radiograph (“Method of recognizing an irradiation field,” European Patent 0,610,605). However, this method can only deal with single-exposed radiographs, and can not be used to completely segment the diagnostically relevant regions where there are two or more radiation fields in a single radiograph, such as the example in FIG. 1(a). To address this limitation, Piet et al disclosed an improved method of detecting the foreground regions (“Method of recognizing one or more irradiation fields,” European Patent 0,742,536). However, both Pieter and Piet failed to teach a method for determining the background regions. Wang et al., showed a method based on Barski's direct exposure detection to determine the image foreground regions (“Method for recognizing multiple irradiation fields in digital radiography,” U.S. Pat. No. 6,212,291). This method, however, still did not fulfill all of the needs of background detection.
Given the drawbacks and limitation of the prior art, there is a need for a method that is exam type independent and that can automatically segment digital radiographic images into anatomy, foreground, and background regions.